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Smart Cities: Data-Driven Solutions to Understand Disruptive Problems in Transportation—The Lisbon Case Study

Author

Listed:
  • Vitória Albuquerque

    (NOVA Information Management School (NOVA IMS), Campus de Campolide, Universidade Nova de Lisboa, 1070-312 Lisbon, Portugal)

  • Ana Oliveira

    (ISTAR-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal)

  • Jorge Lourenço Barbosa

    (ISTAR-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal)

  • Rui Simão Rodrigues

    (ISTAR-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal)

  • Francisco Andrade

    (ISTAR-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal)

  • Miguel Sales Dias

    (NOVA Information Management School (NOVA IMS), Campus de Campolide, Universidade Nova de Lisboa, 1070-312 Lisbon, Portugal
    ISTAR-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal)

  • João Carlos Ferreira

    (ISTAR-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal
    Inov Inesc Inovação—Instituto de Novas Tecnologias, 1000-029 Lisbon, Portugal)

Abstract

Transportation data in a smart city environment is increasingly becoming available. This data availability allows building smart solutions that are viewed as meaningful by both city residents and city management authorities. Our research work was based on Lisbon mobility data available through the local municipality, where we integrated and cleaned different data sources and applied a CRISP-DM approach using Python. We focused on mobility problems and interdependence and cascading-effect solutions for the city of Lisbon. We developed data-driven approaches using artificial intelligence and visualization methods to understand traffic and accident problems, providing a big picture to competent authorities and supporting the city in being more prepared, adaptable, and responsive, and better able to recover from such events.

Suggested Citation

  • Vitória Albuquerque & Ana Oliveira & Jorge Lourenço Barbosa & Rui Simão Rodrigues & Francisco Andrade & Miguel Sales Dias & João Carlos Ferreira, 2021. "Smart Cities: Data-Driven Solutions to Understand Disruptive Problems in Transportation—The Lisbon Case Study," Energies, MDPI, vol. 14(11), pages 1-25, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3044-:d:561292
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    References listed on IDEAS

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    1. Vito Albino & Umberto Berardi & Rosa Maria Dangelico, 2015. "Smart Cities: Definitions, Dimensions, Performance, and Initiatives," Journal of Urban Technology, Taylor & Francis Journals, vol. 22(1), pages 3-21, January.
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    Cited by:

    1. Elena Butsenko, 2022. "How Data Mining Can Improve Road Safety in Cities," Social Sciences, MDPI, vol. 11(3), pages 1-11, March.

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